[BioC] affybatch object too big
beniltoncarvalho at gmail.com
Mon Jun 14 23:14:59 CEST 2010
and oligo may be of interest too (if the annotation package isn't
online, you'll need to build your own via pdInfoBuilder)...
cels = list.celfiles()
rawData = read.celfiles(cels)
rmaData = rma(rawData)
## resFF is a ff object
resFF = exprs(rmaData)
## if you have RAM to store the exprs matrix
resMatrix = resFF
## save in a tab-file
tmp = as.ffdf(resFF)
write.table(tmp, file="results.csv", quote=FALSE, sep="\t")
same applies for Exon and Gene ST arrays.
On 14 June 2010 21:49, James W. MacDonald <jmacdon at med.umich.edu> wrote:
> Hi Noemi,
> Noemi Andor wrote:
>> I have a problem with the loading of an affybatch object from cel-files. I
>> have multiple cel files and want to analyze them all together, yet the
>> amount of data is to big to be loaded. I am interested only in a subset of
>> genes within those cel-files. So I could load the cel-files into 3 or 4 affy
>> objects, then read the expression values of the genes of interest and merge
>> them again. But if I read them separatly, the background correction wil not
>> be global, and I do not know how to read them without background correction:
>> pd=read.AnnotatedDataFrame("BI_samples_1.txt", header=TRUE, row.names=1)
>> a= ReadAffy(filenames = rownames(pData(pd)), phenoData = pd, verbose =
>> e1<-rbind(e206123_at,..., e210684_s_at)
>> If I do the same for BI_samples_2.txt the corresponding e2 will not be
>> comparable to e1, am I right?
>> Would be very greatfull for a good solution to my problem?
> You don't mention your OS, so it is more difficult to suggest. Assuming you
> don't have access to a computer with more memory, the memory-bounded
> solutions are as follows.
> The xps package of Bioconductor. Requires installation of ROOT, but the
> maintainer Christian Stratowa is very active and helpful on this list.
> You will need to go here first to get ROOT.
> then a simple biocLite("xps") should get you started.
> A non-BioC but still R based choice is aroma.affymetrix. More info can be
> found here:
> If you are on Windows or Linux, you could use RMAexpress, which is a
> standalone software to do RMA.
>> best regards,
>> Bioconductor mailing list
>> Bioconductor at stat.math.ethz.ch
>> Search the archives:
> James W. MacDonald, M.S.
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
> Ann Arbor MI 48109-5618
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